Transcranial Doppler ultrasound (TCD) is commonly used to detect emboli in the cerebral circulation. However, current techniques to discriminate between signals from emboli and artefacts are subjective and ambiguous. The radio-frequency (RF) signal provides an extra dimension to the information available from conventional TCD systems, which may help to interpret complex events. Artefacts generated by healthy volunteers and embolic signals recorded from a flow phantom were used to characterize the appearance of the two types of event. Characteristics of events, recorded during and immediately after carotid endarterectomy surgery, were compared to those from known sources. Additional information was provided by the RF signal, on events recorded during TCD monitoring, thus aiding classification. The RF signal may have a role as a gold standard for embolus detection. Embolic signals appear as uniform and predictable shapes within the RF signal, enabling pattern recognition and image processing techniques to be used for their automated detection. Principal component analysis (PCA) has been used to characterize the typical variation in embolic signal shape, within the RF signal, using training sets of in vitro and in vivo data. PCA techniques were also utilised to discriminate between previously unseen embolic and artefact signals. The algorithms developed did not have the accuracy required for their use in a clinical setting but do have the potential to be developed further. Mathematical modelling and in vitro experiments were carried out to assess the feasibility of using coded-excitation and pulse-compression within a TCD system to improve the bandwidth and hence the axial resolution.